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Open AccessArticle

Watershed-Based Evaluation of Automatic Sensor Data: Water Quality and Hydroclimatic Relationships

Department of Physical Geography and Bolin Center for Climate Research, Stockholm University, SE-106 91 Stockholm, Sweden
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Sustainability 2020, 12(1), 396; https://doi.org/10.3390/su12010396
Received: 1 November 2019 / Revised: 27 December 2019 / Accepted: 31 December 2019 / Published: 3 January 2020
(This article belongs to the Special Issue Watershed Modelling and Management for Sustainability)
Water is a fundamental resource and, as such, the object of multiple environmental policies requiring systematic monitoring of its quality as a main management component. Automatic sensors, allowing for continuous monitoring of various water quality variables at high temporal resolution, offer new opportunities for enhancement of essential water quality data. This study investigates the potential of sensor-measured data to improve understanding and management of water quality at watershed level. Self-organizing data maps, non-linear canonical correlation analysis, and linear regressions are used to assess the relationships between multiple water quality and hydroclimatic variables for the case study of Lake Mälaren in Sweden, and its total catchment and various watersheds. The results indicate water discharge from dominant watersheds into a lake, and lake water temperature as possible proxies for some key water quality variables in the lake, such as blue-green algae; the latter is, in turn, identified as a potential good proxy for lake concentration of total nitrogen. The relationships between water discharges into the lake and lake water quality dynamics identify the dominant contributing watersheds for different water quality variables. Seasonality also plays an important role in determining some possible proxy relationships and their usefulness for different parts of the year. View Full-Text
Keywords: water quality; water discharge; hydroclimate; data mining; automatic sensor; monitoring; watershed; lake Mälaren; Stockholm region water quality; water discharge; hydroclimate; data mining; automatic sensor; monitoring; watershed; lake Mälaren; Stockholm region
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Cantoni, J.; Kalantari, Z.; Destouni, G. Watershed-Based Evaluation of Automatic Sensor Data: Water Quality and Hydroclimatic Relationships. Sustainability 2020, 12, 396.

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